Search (169 results, page 1 of 9)

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Abstract

Of h-type indices available now, the g-index is an important one in that it not only keeps some advantages of the h-index but also counts citations from highly cited articles. However, the g-index has a drawback that one has to add fictitious articles with zero citation to calculate this index in some important cases. Based on an alternative definition without introducing fictitious articles, an analytical method has been proposed to calculate the g-index based approximately on the h-index and the e-index. If citations for a scientist are ranked by a power law, it is shown that the g-index can be calculated accurately by the h-index, the e-index, and the power parameter. The relationship of the h-, g-, and e-indices presented here shows that the g-index contains the citation information from the h-index, the e-index, and some papers beyond the h-core.

Object

h-index
g-index
e-index

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Abstract

Based on earlier results about the shifted Lotka function, we prove an implicit functional relation between the Hirsch index (h-index) and the total number of sources (T). It is shown that the corresponding function, h(T), is concavely increasing. Next, we construct an implicit relation between the h-index and the impact factor IF (an average number of items per source). The corresponding function h(IF) is increasing and we show that if the parameter C in the numerator of the shifted Lotka function is high, then the relation between the h-index and the impact factor is almost linear.

Object

h-index

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Abstract

Purpose - This review aims to show, broadly, how the h-index has become a subject of widespread debate, how it has spawned many variants and diverse applications since first introduced in 2005 and some of the issues in its use. Design/methodology/approach - The review drew on a range of material published in 1990 or so sources published since 2005. From these sources, a number of themes were identified and discussed ranging from the h-index's advantages to which citation database might be selected for its calculation. Findings - The analysis shows how the h-index has quickly established itself as a major subject of interest in the field of bibliometrics. Study of the index ranges from its mathematical underpinning to a range of variants perceived to address the indexes' shortcomings. The review illustrates how widely the index has been applied but also how care must be taken in its application. Originality/value - The use of bibliometric indicators to measure research performance continues, with the h-index as its latest addition. The use of the h-index, its variants and many applications to which it has been put are still at the exploratory stage. The review shows the breadth and diversity of this research and the need to verify the veracity of the h-index by more studies.

Date

8. 1.2011 19:22:13

Object

h-index

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Abstract

The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.

Object

h-index

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Abstract

This study examines longitudinal trends in the university-industry-government (UIG) relationship on the web in the Korean context by using triple helix (TH) indicators. The study considers various Internet resources, including websites/documents, blogs, online cafes, Knowledge-In (comparable to Yahoo! Answers), and online news sites, by employing webometric and co-word analysis techniques to ascertain longitudinal trends in the UIG relationship, which have received considerable attention in the last decade. The results indicate that the UIG relationship varied according to the government's policies and that there was some tension in the longitudinal UIG relationship. Further, websites/documents and blogs were the most reliable sources for examining the strength of and variations in the bilateral and trilateral UIG relationships on the web. In addition, web-based T(uig) values showed a stronger trilateral relationship and larger variations in the UIG relationship than Science Citation Index-based T(uig) values. The results suggest that various Internet resources (e.g., advanced search engines, websites/documents, blogs, and online cafes), together with TH indicators, can be used to explore the UIG relationship on the web.

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Abstract

Citation analysis of documents retrieved from the Medline database (at the Web of Knowledge) has been possible only on a case-by-case basis. A technique is presented here for citation analysis in batch mode using both Medical Subject Headings (MeSH) at the Web of Knowledge and the Science Citation Index at the Web of Science (WoS). This freeware routine is applied to the case of "Brugada Syndrome," a specific disease and field of research (since 1992). The journals containing these publications, for example, are attributed to WoS categories other than "cardiac and cardiovascular systems", perhaps because of the possibility of genetic testing for this syndrome in the clinic. With this routine, all the instruments available for citation analysis can now be used on the basis of MeSH terms. Other options for crossing between Medline, WoS, and Scopus are also reviewed.

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Date

22. 8.2014 17:11:29

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Date

8. 7.2015 22:00:42

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Abstract

Die Arbeit analysiert die dynamische Entwicklung und den Gebrauch von Thesaurusbegriffen. Zusätzlich konzentriert sie sich auf die Faktoren, die die Zahl von Indexbegriffen pro Dokument oder Zeitschrift beeinflussen. Als Untersuchungsobjekt dienten der MeSH und die entsprechende Datenbank "MEDLINE". Die wichtigsten Konsequenzen sind: 1. Der MeSH-Thesaurus hat sich durch drei unterschiedliche Phasen jeweils logarithmisch entwickelt. Solch einen Thesaurus sollte folgenden Gleichung folgen: "T = 3.076,6 Ln (d) - 22.695 + 0,0039d" (T = Begriffe, Ln = natürlicher Logarithmus und d = Dokumente). Um solch einen Thesaurus zu konstruieren, muss man demnach etwa 1.600 Dokumente von unterschiedlichen Themen des Bereiches des Thesaurus haben. Die dynamische Entwicklung von Thesauri wie MeSH erfordert die Einführung eines neuen Begriffs pro Indexierung von 256 neuen Dokumenten. 2. Die Verteilung der Thesaurusbegriffe erbrachte drei Kategorien: starke, normale und selten verwendete Headings. Die letzte Gruppe ist in einer Testphase, während in der ersten und zweiten Kategorie die neu hinzukommenden Deskriptoren zu einem Thesauruswachstum führen. 3. Es gibt ein logarithmisches Verhältnis zwischen der Zahl von Index-Begriffen pro Aufsatz und dessen Seitenzahl für die Artikeln zwischen einer und einundzwanzig Seiten. 4. Zeitschriftenaufsätze, die in MEDLINE mit Abstracts erscheinen erhalten fast zwei Deskriptoren mehr. 5. Die Findablity der nicht-englisch sprachigen Dokumente in MEDLINE ist geringer als die englische Dokumente. 6. Aufsätze der Zeitschriften mit einem Impact Factor 0 bis fünfzehn erhalten nicht mehr Indexbegriffe als die der anderen von MEDINE erfassten Zeitschriften. 7. In einem Indexierungssystem haben unterschiedliche Zeitschriften mehr oder weniger Gewicht in ihrem Findability. Die Verteilung der Indexbegriffe pro Seite hat gezeigt, dass es bei MEDLINE drei Kategorien der Publikationen gibt. Außerdem gibt es wenige stark bevorzugten Zeitschriften."

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Abstract

This study explores the factors influencing citations to Internet studies by assessing the relative explanatory power of three perspectives: normative theory, the social constructivist approach, and a natural growth mechanism. Using data on 7,700+ articles of Internet studies published in 100+ Social Sciences Citation Index (SSCI)-listed journals in 2000-2009, the study adopted a multilevel model to disentangle the impact between article- and journal-level factors on citations. This research strategy resulted in a number of both expected and surprising findings. The primary determinants for citations are found to be journal-level factors, accounting for 14% of the variances in citations of Internet studies. The impact of some, if not all, article-level factors on citations are moderated by journal-level factors. Internet studies, like studies in other areas (e.g., management, demography, and ecology), are cited more for rhetorical purposes, as suggested by the social constructivist approach, rather than as a form of reward, as argued by normative theory. The impact of time on citations varies across journals, which creates a growing "citation gap" for Internet studies published in journals with different characteristics.

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Abstract

The cognitive and social structures, and publication practices, of the humanities have been studied bibliometrically for the past 50 years. This article explores the conceptual frameworks, methods, and data sources used in bibliometrics to study the nature of the humanities, and its differences and similarities in comparison with other scientific domains. We give a historical overview of bibliometric scholarship between 1965 and 2018 that studies the humanities empirically and distinguishes between two periods in which the configuration of the bibliometric system differs remarkably. The first period, 1965 to the 1980s, is characterized by bibliometric methods embedded in a sociological theoretical framework, the development and use of the Price Index, and small samples of journal publications from which references are used as data sources. The second period, the 1980s to the present day, is characterized by a new intellectual hinterland-that of science policy and research evaluation-in which bibliometric methods become embedded. Here metadata of publications becomes the primary data source with which publication profiles of humanistic scholarly communities are analyzed. We unpack the differences between these two periods and critically discuss the analytical avenues that different approaches offer.

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Abstract

Literature citation analysis plays a very important role in bibliometrics and scientometrics, such as the Science Citation Index (SCI) impact factor, h-index. Existing citation analysis methods assume that all citations in a paper are equally important, and they simply count the number of citations. Here we argue that the citations in a paper are not equally important and some citations are more important than the others. We use a strength value to assess the importance of each citation and propose to use the regression method with a few useful features for automatically estimating the strength value of each citation. Evaluation results on a manually labeled data set in the computer science field show that the estimated values can achieve good correlation with human-labeled values. We further apply the estimated citation strength values for evaluating paper influence and author influence, and the preliminary evaluation results demonstrate the usefulness of the citation strength values.

Date

22. 8.2014 17:12:35

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Abstract

We investigate the extent to which open-access (OA) journals and articles in biology, computer science, economics, history, medicine, and psychology are indexed in each of 11 bibliographic databases. We also look for variations in index coverage by journal subject, journal size, publisher type, publisher size, date of first OA issue, region of publication, language of publication, publication fee, and citation impact factor. Two databases, Biological Abstracts and PubMed, provide very good coverage of the OA journal literature, indexing 60 to 63% of all OA articles in their disciplines. Five databases provide moderately good coverage (22-41%), and four provide relatively poor coverage (0-12%). OA articles in biology journals, English-only journals, high-impact journals, and journals that charge publication fees of $1,000 or more are especially likely to be indexed. Conversely, articles from OA publishers in Africa, Asia, or Central/South America are especially unlikely to be indexed. Four of the 11 databases index commercially published articles at a substantially higher rate than articles published by universities, scholarly societies, nonprofit publishers, or governments. Finally, three databases-EBSCO Academic Search Complete, ProQuest Research Library, and Wilson OmniFile-provide less comprehensive coverage of OA articles than of articles in comparable subscription journals.

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Abstract

Purpose - The purpose of this paper is to analyse the global scientific outputs of ontology research, an important emerging discipline that has huge potential to improve information understanding, organization, and management. Design/methodology/approach - This study collected literature published during 1900-2012 from the Web of Science database. The bibliometric analysis was performed from authorial, institutional, national, spatiotemporal, and topical aspects. Basic statistical analysis, visualization of geographic distribution, co-word analysis, and a new index were applied to the selected data. Findings - Characteristics of publication outputs suggested that ontology research has entered into the soaring stage, along with increased participation and collaboration. The authors identified the leading authors, institutions, nations, and articles in ontology research. Authors were more from North America, Europe, and East Asia. The USA took the lead, while China grew fastest. Four major categories of frequently used keywords were identified: applications in Semantic Web, applications in bioinformatics, philosophy theories, and common supporting technology. Semantic Web research played a core role, and gene ontology study was well-developed. The study focus of ontology has shifted from philosophy to information science. Originality/value - This is the first study to quantify global research patterns and trends in ontology, which might provide a potential guide for the future research. The new index provides an alternative way to evaluate the multidisciplinary influence of researchers.

Date

20. 1.2015 18:30:22
17. 9.2018 18:22:23

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Abstract

The h-index can be a useful metric for evaluating a person's output of Internet media. Here I advocate and demonstrate adaption of the h-index and the g-index to the top video content creators on YouTube. The h-index for Internet video media is based on videos and their view counts. The h-index is defined as the number of videos with >=h × 10**5 views. The g-index is defined as the number of videos with >=g × 10**5 views on average. When compared with a video creator's total view count, the h-index and g-index better capture both productivity and impact in a single metric.

Object

h-index
g-index

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Date

22. 3.2013 19:45:49

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Abstract

Purpose The purpose of this paper is to analyze the relationship between dissemination of research papers on Twitter and its influence on research impact. Design/methodology/approach Four types of journal Twitter accounts (journal, owner, publisher and no Twitter account) were defined to observe differences in the number of tweets and citations. In total, 4,176 articles from 350 journals were extracted from Plum Analytics. This altmetric provider tracks the number of tweets and citations for each paper. Student's t-test for two-paired samples was used to detect significant differences between each group of journals. Regression analysis was performed to detect which variables may influence the getting of tweets and citations. Findings The results show that journals with their own Twitter account obtain more tweets (46 percent) and citations (34 percent) than journals without a Twitter account. Followers is the variable that attracts more tweets (ß=0.47) and citations (ß=0.28) but the effect is small and the fit is not good for tweets (R2=0.46) and insignificant for citations (R2=0.18). Originality/value This is the first study that tests the performance of research journals on Twitter according to their handles, observing how the dissemination of content in this microblogging network influences the citation of their papers.

Date

20. 1.2015 18:30:22

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Abstract

"Thomson Reuters' citation indexes i.e. SCI, SSCI and AHCI are said to be "authoritative". Due to the huge influence of these databases on global academic evaluation of productivity and impact, Terje Tüür-Fröhlich decided to conduct case studies on the data quality of Social Sciences Citation Index (SSCI) records. Tüür-Fröhlich investigated articles from social science and law. The main findings: SSCI records contain tremendous amounts of "trivial errors", not only misspellings and typos as previously mentioned in bibliometrics and scientometrics literature. But Tüür-Fröhlich's research documented fatal errors which have not been mentioned in the scientometrics literature yet at all. Tüür-Fröhlich found more than 80 fatal mutations and mutilations of Pierre Bourdieu (e.g. "Atkinson" or "Pierre, B. and "Pierri, B."). SSCI even generated zombie references (phantom authors and works) by data fields' confusion - a deadly sin for a database producer - as fragments of Patent Laws were indexed as fictional author surnames/initials. Additionally, horrific OCR-errors (e.g. "nuxure" instead of "Nature" as journal title) were identified. Tüür-Fröhlich´s extensive quantitative case study of an article of the Harvard Law Review resulted in a devastating finding: only 1% of all correct references from the original article were indexed by SSCI without any mistake or error. Many scientific communication experts and database providers' believe that errors in databanks are of less importance: There are many errors, yes - but they would counterbalance each other, errors would not result in citation losses and would not bear any effect on retrieval and evaluation outcomes. Terje Tüür-Fröhlich claims the contrary: errors and inconsistencies are not evenly distributed but linked with languages biases and publication cultures."

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Abstract

The h-index was devised to represent a scholar's contributions to his field with respect to the number of publications and citations. It does not, however, take into consideration the scholar's position in the authorship list. I recommend a new supplementary index to score academics, representing the relative contribution to the papers with impact, be reported alongside the h-index. I call this index the AP-index, and it is simply defined as the average position in which an academic appears in authorship lists, on articles that factor in to that academic's h-index.

Object

h-index

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Abstract

Purpose The purpose of this paper is to analyse the author self-citation behavior in the field of Library and Information Science. Various factors governing the author self-citation behavior have also been studied. Design/methodology/approach The 2012 edition of Social Science Citation Index was consulted for the selection of LIS journals. Under the subject heading "Information Science and Library Science" there were 84 journals and out of these 12 journals were selected for the study based on systematic sampling. The study was confined to original research and review articles that were published in select journals in the year 2009. The main reason to choose 2009 was to get at least five years (2009-2013) citation data from Web of Science Core Collection (excluding Book Citation Index) and SciELO Citation Index. A citation was treated as self-citation whenever one of the authors of citing and cited paper was common, i.e., the set of co-authors of the citing paper and that of the cited one are not disjoint. To minimize the risk of homonyms, spelling variances and misspelling in authors' names, the authors compared full author names in citing and cited articles. Findings A positive correlation between number of authors and total number of citations exists with no correlation between number of authors and number/share of self-citations, i.e., self-citations are not affected by the number of co-authors in a paper. Articles which are produced in collaboration attract more self-citations than articles produced by only one author. There is no statistically significant variation in citations counts (total and self-citations) in works that are result of different types of collaboration. A strong and statistically significant positive correlation exists between total citation count and frequency of self-citations. No relation could be ascertained between total citation count and proportion of self-citations. Authors tend to cite more of their recent works than the work of other authors. Total citation count and number of self-citations are positively correlated with the impact factor of source publication and correlation coefficient for total citations is much higher than that for self-citations. A negative correlation exhibits between impact factor and the share of self-citations. Of particular note is that the correlation in all the cases is of weak nature. Research limitations/implications The research provides an understanding of the author self-citations in the field of LIS. readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study. Originality/value Readers are encouraged to further the study by taking into account large sample, tracing citations also from Book Citation Index (WoS) and comparing results with other allied subjects so as to validate the robustness of the findings of this study.

Date

20. 1.2015 18:30:22